Adaptive shared computing infrastructure for application server-based deployments

ABSTRACT

An adaptive system for dynamically provisioning a shared computing infrastructure among a plurality of software applications and a plurality of types of applications servers providing run-time environments for the software applications. The system includes computing engines assigned to execute instances of the software applications, clients accessing the computing engines to request and receive services from the software applications, and a broker device that dynamically allocates engines domains for executing the software applications. The broker device includes an optimization module for allocating the computing engines to the domains, and a configuration manager for configuring the engines. The configuration manager reconfigures a computing engine by halting a current instance of a first software application, and by loading and starting an instance of a second software application. The system is capable of reconfiguring software applications running in environments provided by different types of software applications servers.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit under 35 U.S.C. § 119(e) ofU.S. Provisional Application No. 60/688,418, filed on Jun. 7, 2005,which is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention is directed to a system and method for dynamicallyallocating and provisioning shared computing resources in a distributedcomputing environment. More specifically, the present invention isdirected to a system and method for dynamically allocating andprovisioning shared computing resources among a plurality of differenttypes of software applications in run-time environments provided by aplurality of different types of application servers.

BACKGROUND OF THE INVENTION

The global marketplace is forcing companies to respond quickly todynamic market conditions while reducing costs. Businesses increasinglymust have the ability to meet, or beat, competitors by introducing newand innovative products and services. These new offerings are oftencustomer-facing and transaction-oriented, and introduce additionalcomplexity and higher levels of volatility for the enterprise computingresources called upon to provision these products and services. Highertransaction volumes and demands for improved response times create anever-increasing need for computing resources.

In a conventional enterprise computing environment, computing resourcesare usually manually assigned and provisioned to support variousapplications. This approach creates several problems. As the assignedresources are generally fixed at a point in time to meet a currentdemand level, the conventional enterprise computing environment isill-equipped to adapt over time to meet increasing demand levels forsome applications and decreasing demand levels for others. In order tomeet minimum service requirements, computing resources are oftenassigned and provisioned according to peak-level demands. As a result,during periods of less than peak-level demands, computing resources areunderutilized.

With the advent of grid computing, conventional enterprise computingenvironments have been adapted to “virtualize” applications so thatcomputing resources may be dynamically provisioned to applications inresponse to current demand levels. For example, the GRIDSERVER VirtualEnterprise Edition adaptive grid infrastructure software available fromDataSynapse, New York, N.Y. provides a computing operating environmentthat virtualizes application and data services, independent of specificsystem resources. Client applications submit service requests to thegrid environment, and GRIDSERVER dynamically provisions services onspecific system resources in the grid to meet the service requests. Forexample, requests from multiple client applications cause GRIDSERVER tocreate multiple service instances to handle the requests in parallel ondifferent computing resource nodes in the computing resources grid. As aresult, underutilization of resources can be substantially reduced, andservice levels can be commensurately improved.

GRIDSERVER has been particularly effective at providing a virtualizedcomputing environment that adapts to meet resource demands forcomputing-intensive processes. It would be of further benefit to developa virtualized computing environment that effectively adapts to meetresource demands for high throughput, low latency transactionalapplications such as distributed web applications and otherservices-based application. In addition, it would be of further benefitto develop a virtualized computing environment that adaptivelyprovisions computing resources for web and other services-basedapplications supported by a variety of different types of applicationservers.

SUMMARY OF THE INVENTION

The present invention is directed to a system and method for adaptivelyprovisioning a shared computing infrastructure to support a plurality ofsoftware applications and a plurality of types of applications serverseach providing a run-time environment for one or more of the softwareapplications. The system includes computing engines assigned to executeinstances of the plurality of software applications, clients accessingthe computing engines to request and receive services from the softwareapplications, and a broker that dynamically allocates computing enginesto the clients for executing the software applications.

The broker includes an optimization module for periodically determiningan optimal allocation of the computing engines to the softwareapplications and applications servers. To reallocate resources based onan optimal allocation, the broker device also includes a configurationmanager for reconfiguring a computing engine by halting a currentinstance of a software application of a first type, and for loading andstarting an instance of a software application of a second type, wherethe software application of the first type and the software applicationof the second type may be configured to operate in run-time environmentscreated by different types of software application servers. In such aheterogeneous computing environment, the broker is fully flexible toallocate software applications supported by a variety of types ofapplication servers.

For web applications, for example, where the client is simply a webbrowser or other http client seeking to connect to a web application orweb service, the system may further include a router or “virtualgateway” for alternatingly routing requests among the computing engines,for example, so that at least one of the number of service requests perengine and the service load per engine are balanced across the engines.A monitor of the broker periodically collects statistical informationfrom one or more of the engines, the clients and the router. Thestatistical information is used then used by the broker together with ausage policy to determine the optimal resource allocation.

In addition, the broker device includes a software distribution modulefor retrieving components of the software applications and applicationsservers from an archival database so that these components may bedistributed to and loaded on the engines.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of the present invention will be morereadily apparent from the following detailed description and drawings ofillustrative embodiments of the invention wherein like reference numbersrefer to similar elements throughout the several views and in which:

FIG. 1A provides a schematic diagram illustrating an architecture forthe present invention;

FIG. 1B provides a schematic diagram illustrating an alternate view ofarchitecture for the present invention;

FIG. 1C provides a schematic diagram illustrating a third view of thearchitecture for the present invention;

FIGS. 2, 3A and 3B illustrate exemplary web pages produced by anadministrative tool used in conjunction with the present invention;

FIG. 4A provides a schematic diagram illustrating domain types supportedby the present invention;

FIG. 4B illustrates a virtual gateway for balancing traffic for webapplications and services;

FIG. 4C illustrates an exemplary web page of a domain wizard of theadministrative interface that identifies container types;

FIG. 4D illustrates an exemplary web page of the domain wizard forcreating or editing a web application domain

FIG. 5A illustrates an exemplary policy editor page of theadministrative tool of FIG. 2 for setting minimum and maximum values forengine allocations to domains and groups;

FIG. 5B provides an example of time-of-day dependent grid allocations ascontrolled by a policy of the present invention;

FIG. 5C illustrates an exemplary policy wizard web page that may be usedto set performance-based resource allocation constraints;

FIG. 5D provides an example distribution of engines allocated tooperating domains.

FIG. 6A provides a schematic diagram illustrating elements of an enginecomponent of the present invention;

FIG. 6B provides flowcharts illustrating the steps for executing anengine lifecycle;

FIG. 7A provides a schematic diagram illustrating elements implementinga client component of the present invention FIG. 7B provides a schematicdiagram illustrating the creation of threads on an engine as managed bythe client of FIG. 7A;

FIG. 8A provides a schematic diagram illustrating broker-initiatedprovisioning of engines dedicated to clients;

FIGS. 8B and 8C provide schematic diagrams illustrating broker-initiatedprovisioning of engines shared by clients;

FIG. 8D provides a schematic diagram illustrating client-initiatedprovisioning of engines;

FIG. 9A provides a schematic diagram illustrating how performancestatistics are compiled by the broker;

FIG. 9B provides a schematic diagram illustrating how performancestatistics are collected by a client or engine;

FIGS. 9C and 9D provide a sample lists of the statistics compiled by thebroker in FIG. 9A;

FIG. 9E illustrates an exemplary “dashboard” web page of theadministrative tool;

FIG. 9F illustrates an exemplary web page reporting a measured statisticfor an engine; and

FIG. 10 presents a flow diagram illustrating an adaptive provisioningprocess according to the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is directed to an application virtualization andprovisioning (AVP) platform that creates a highly adaptive sharedcomputing infrastructure. Within this infrastructure, applicationservers and other service-oriented components are hosted and virtualizedon shared computing resources, and are adaptively provisioned andactivated in response to demand. The shared computing resources may begeographically localized, or may be distributed over a wide geographicarea and managed as a computing grid. See Mark Baker et al., Grids andGrid technologies for wide-are distributed computing,” Softw. Pract.Exper., John Wiley & Sons, Ltd., 2002, which is hereby incorporated byreference.

Application virtualization enables the removal of static, host-specificconfiguration dependence from the application environment by using theAVP platform to automatically and adaptively allocate, configure, start,deploy, monitor and manage software applications and services. Explicitusage policies are defined that guide provisioning and dynamicallocation of the shared computing resources The configuration ofsoftware applications and services is in particular enabled by a brokercomponent of the AVP platform that stores applications servers,configurations and software applications in a central repository fordeployment to the shared computing resources as required according tothe resource allocation, and manages the allocation of the sharedcomputing resources based on the usage policies. This component alsoincludes a facility for deploying new application code to the sharedcomputing resources while existing applications are running in thecurrently-allocated configurations.

The AVP platform is directed to managing “domains,” which may comprisean enterprise business application, utility service or data source thatis allowed a certain percentage of available resources at a specifiedtime, based on the usage policy. Domains consist of the artifacts thatmake up the application, service or data source (e.g., web archive (WAR)files making up a web application), and may be classified among threedomain types: service domains, data domains and web domains.

Service domains are used to virtualize Java programming objects,including plain old Java objects (POJOs), Spring Beans and EnterpriseJava Beans (EJBs), by turning them into services. These virtualizedservices may then be accessed by Java clients via dynamic proxies.

Data domains provide data services such as databases or scalable cachingservices. Data domains may preferably be implemented, for example, asJBOSS cache and TANGOSOL's COHERENCE cache.

Web domains provide web applications and services such as web servers,messaging brokers, message-driven services and other services thattypically require multiple running instances at any given point in time.Web domains include collections of application services that areaccessible over the Internet via communications based on the hypertexttransfer protocol (http).

Domains can be launched or hosted on one or more application servers (or“containers”). Containers are effectively “sandboxes” for hosting thedomains. Each container type is capable of hosting one or more domaintype, and a given domain can be launched by any container that supportsits type. For example, a JBOSS container can host web application, webservice and EJB service domains. Other container types may include butare not necessarily limited to APACHE TOMCAT containers, CAUCHO RESINcontainers, IBM WEBLOGIC containers, and other generic containerssupported by the AVP platform.

A service-level policy, or consistent set of rules, is applied todictate the operation and division of computing resources. Theservice-level policy may be defined for example by software applicationand/or by user group, and may be conditioned on certain performancerequirements including but not necessarily limited to response time,throughput and minimum/maximum allocation of computing resources(“percentage of grid”). In accordance with the defined service-levelpolicy, the AVP platform operates to provision and activate servicesaccording to demand for improved performance and utilization ofresources.

A system-level architecture for the AVP platform 100 is illustrated inFIG. 1A. The architecture includes four fundamental elements: clients10, engines 20 associated with domains 40, and a broker 30. Clients 10 aand 10 b are software applications that access and utilize the domains40. Engines 20 are processes that provision and run softwareapplications in the domains 40. The broker 30 is a software applicationthat carries out policy-driven resource allocation (e.g., allocation ofengines 20 to domains 40 and clients 10 a) and performance monitoring.Each of the clients 10 a, engines 20 and broker 30 may be implemented onconventional INTEL and/or SUN/SPARC hardware platforms running, forexample, WINDOWS, WINDOWS SERVER, SOLARIS, RED HAT Linux or RED HATEnterprise Linux operating systems

As illustrated in FIG. 1A, clients 10 a and engines 30 both interactwith the broker 30. The broker 30 assigns domains 40 to engines 20, andprovides information for example to JAVA clients 10 a that instructs theclients how to access to the engines 20. Thereafter, JAVA clients 10 aare able to submit service requests directly to the connected engines20. Http clients 10 b submit service requests via a router (“Vgateway31”), which acts as a virtual gateway and load balancer for directingthe service requests to engines 20 running web service or webapplication domains.

FIG. 1B illustrates an alternate view of the architecture for the AVPplatform 100. AVP platform 100 dynamically assigns and provisionscomputing resources 21 among software applications 41 supported byapplication servers 41 a by configuring domains 42, 43 and 44. AVPplatform 100 optimizes the assignment of resources 21 among theapplications 41 subject to constraints 60 which may include, forexample, service-level policies associated with the domains 42, 43, 44,and/or with user groups seeking access to the domains, service levelagreements (“SLAs”) associated with the domains 42, 43, 44 and or usergroups, performance statistics periodically collected from engines,clients and other components of the AVP platform 100, and servicedemands predicted from the usage statistics.

FIG. 1C illustrates a third view of the architecture for the AVPplatform 100. Computing resources are represented by grid nodes 25,which may each include one or more host computers. Broker 30 allocatesand configures one or more engines 20 to run on each of the grid nodes25. Each engine 20 manages a container 26 that serves as an environmentfor running an application, service or data source, and preferablycollects and reports performance statistics for the application, serviceor data source (for example, by Java Management Extension (JMX) proxyfor Java 2 Platform, Enterprise Edition (J2EE) applications), andpreferably binds with a container software development kit (SDK) withinan administrative interface (not shown) that may be used to configurethe containers 26.

Broker 30 also configures a daemon 22 that runs on each host computer ineach grid node 26 that monitors the host, manages the engines 22 thatare running on the host, and deploys binary code provided by the broker30 for running a container (or applications server) 26 and/or anapplication, service or data source to be run by the container 26. Inaddition, broker 30 collects performance statistics provided by theengines 20 (and/or by clients 10 a and Vgateway 31) for storage in adatabase 39, for reporting and/or as inputs to the allocationoptimization. Broker 30 may also provide failover services forreallocating an application, service or data source from a failed hostcomputer to an operating host computer.

AVP platform 100 of FIGS. 1A, 1B and 1C further includes anadministrative interface (not shown) of the broker 30 that enables aplatform administrator to define, register and deploy domains, to manageworkloads and to configure the AVP platform environment. By way ofexample, FIG. 2 illustrates a broker web page of the administrativeinterface that provides access to a variety of wizards available forcreating data, web and service domains, and for establishing policy.

In addition, the administrative interface allows the platformadministrator to monitor and manage various performance metrics,including but not necessarily limited to throughput, latency, resourceusage, and exceptions. For example, FIG. 3A illustrates a “dashboard”page of the administrative interface that provides a pie chartindicating a current allocation of resources among domains, and FIG. 3Billustrates a “broker monitor” page of the administrative interface thatgraphs the allocation of resources among domains over time.

Domains

As illustrated in FIG. 4A, the AVP platform 100 is directed to managethree types of domains: service domains 45, web domains 46 and datadomains 47.

Web Domains

Web domains 45 provide web applications and services, for example,including web servers, messaging brokers, message-driven services andother services that typically require multiple running instances. Webdomains represent any collection of application services that areaccessible via http, and can effectively represent any object or processthat can be started, stopped and interrogated for its current load.Types of web domains include web applications accessible via a browser,and web services made available via simple object access protocol (SOAP)over http.

Web domains are preferably targeted for J2EE application servers. Forexample, an existing J2EE application may be represented as a webservice, with an application cluster size varying between 2 and 5 nodes,base on policy. The physical locations of the web domain instances aredecided by the AVP platform 100 at runtime, and the resources areprovisioned dynamically. The AVP platform 100 then instantiates eachdomain on one or more grid nodes. The policy that dictates how manyinstances are created, and at what time they are created, are dictatedby a service-level policy that is maintained by the broker 30.

As illustrated in FIGS. 1A and 4B, web clients 10 b may preferablyaccess web domains 40 via a virtual gateway router (Vgateway 31).VGateway 31 is preferably implemented as part of the broker 30, andfunctions essentially as a smart load balancer, routing web servicerequests and responses from external clients to resource virtualizedengines. Unlike conventional static load balancers, Vgateway 31 isinformed when the configuration of host computers 23 and/or domains 40changes, and adjusts its load balancing scheme accordingly.

Service Domains

Service domains 46 include a collection of interfaces that can bevirtualized across distributed computing resources (“grid resources”).By grouping these resources within a service domain, specific policiescan be set to determine how many resources each service domain will beallowed to consume. JAVA-based service domains 45 may be defined, forexample, using J2EE, plain old JAVA objects (“POJOs”) or the Springframework

Service domains 45 may be used, for example, to define any standard JAVAclass or Enterprise Java Bean (EJB). No proprietary applicationprogramming interface (API) or class format is required to virtualizethe associated Java service. For example, POJOs can be defined withapplication context, or the complete and necessary environment formaking the associated Java object instance work correctly. For example,a JAVA class that represents a business service would be defined withaccess to database connections and messaging services in order toperform the required processing. Preferably, a simple Extensible MarkupLanguage (XML) format is provided for declaring the proper context foreach object.

Among supported service domain types, the POJO domain type is thesimplest to construct. Any JAVA class can be included in a POJO servicedomain. In addition, a Spring service domain type may preferably besupported. See Rod Johnson, Introduction to the Spring Framework, May2005, available atwww.theserverside.com/articles/article.tss?l=SpringFramework, which ishereby incorporated by reference. The Spring framework simplifies J2EEdevelopment by using POJOs instead of EJBs, and allowing for theabstraction and encapsulation of implementation dependent components(for example, Hibernate and JDBC mapping tools). In addition, thisframework allows for dynamic proxy-based aspect oriented programming(AOP). AOP is a programming facility that allows developers the abilityto inject logging, transaction, security and transaction capabilitiesacross modules and components. The Spring framework also uses AOP toprovided declarative transaction management for POJOS. For legacycomponents that are packaged as EJBs, an EJB service domain allows forvirtualized access to EJB functionality.

Data Domains

Data domains 47 of FIG. 4A provide data services such as databases orscalable caching services. These services are essentially clientless, asno gateway or proxy to the services in provided via the broker. Instead,the AVP platform may provide a centralized lookup, for example, such asa Java Naming and Directory Interface (JNDI) that allows clients todiscover and connect to these domains.

Creating Domains

According to the principles of the present invention, domains arelaunched or hosted on one or more applications servers, or containers.Each container type is capable of hosting one or more domain types, anda given domain can be launched by any container that supports its type.FIG. 4C provides an exemplary listing of container types supported by adomain wizard of the administrative interface. For example, a JBOSScontainer can support web application, web service and EJB servicedomains. Other container types include but are not limited to APACHETOMCAT containers, CAUCHO RESIN containers, IBM WEBLOGIC containers, andother generic containers supported by the AVP platform. Theadministrative interface preferably includes a container softwaredevelopment kit (SDK) enabling the addition of additional containertypes as required.

Domains may be created for example by means of a domain wizard withinthe administrative interface. FIG. 4D illustrates an exemplary web pageof the domain wizard for creating or editing a web application domainthat deploys a specified web application. As illustrated in FIG. 4D, theweb application domain may be newly created or modified by selecting andspecifying an appropriate container, and by specifying domain settings,associated archive files (for example, JAVA archive (JAR), Enterprisearchive (EAR) or web archive (WAR) files), servlets and EnterpriseJAVABEANS (EJBs). In addition, tracked statistics for associatedservice-level policies may be specified. For web applications and webservices, URL patterns to be used by the Vgateway 31 of FIG. 1A may alsobe specified.

Policy and Resource Allocation

The broker 30 of FIG. 1A is configured with a service-level policy thatprovides a consistent set of rules for the assignment and allocation ofcomputing resources from the resource grid. This policy enables thebroker 30 to select a resource allocation among the domains. In theabsence of this policy, the broker may operate to assign an equalpercentage of grid resources to each of the domains.

The service-level policy defines a hierarchical, constraint-baseddivision of computing resources in the grid. For example, a first levelof partitioning may be by domain, followed by a second level ofpartitioning by user group. Additional and/or alternate partitioningcriteria may be arbitrarily selected (for example, partitioning by workproject), all of which are fully contemplated within the scope of thepresent invention.

The service-level policy will generally define a minimum number andmaximum engines that should be allocated for each domain, either interms of a number of engines or a percentage of available engines. A“minimum allocation percent” specifies a least amount of resource alwaysheld by an associated domain. If no clients are running, the rule may beexcepted in order to make resources available to other grid clients (the“minimum allocation percent” is set to zero, so that no resources areassigned unless no other clients are running). However, these resourcesare relinquished as soon as a non-running client starts up. If theminimum allocation percents for grid clients do not sum to 100%, and alltypes of grid clients are active, the broker may continuouslyredistribute resources to optimize service-level agreements (SLAs) forthe grid clients or domain.

A “maximum allocation percent” specifies a cap on the amount ofresources to be given to an associated domain. This maximum ispreferably enforced even if idle resources are available. As illustratedin FIG. 5A, the administrative interface preferably provides an editorfor editing the minimum and maximum engine allocations for domains.

The broker may in addition apply a policy schedule that indicates howpolicies are to be applied over the course of a day. As illustrated forexample in FIG. 5B, the grid resources assigned to a domain 48 for anapplication varies with time. Domain 48 a at 8:15 AM is allocated fourcomputing engines 20 from the grid. At 8:30 AM, the number of allocatedengines in domain 48 b is reduced to three engines 20. At 8:45 AM, thenumber of engines allocated to domain 48 c is increased to five engines20. Domains may also be assigned priority weights which indicate howresources are to be divided when there is resource contention.

Once the minimum and maximum number of engines is established, thebroker 30 proceeds to provision resources to a minimum level. The broker30 may choose to allocate more than the minimum number of engines to adomain if there is a statistical rule that can be used to understand theperformance of the application. For example, if queue size can bemeasured as an indication of current load on the application, a rule canbe established for adding an additional engine when the average queuesize for all engines in the domain over a specified time intervalexceeds a specified level. In addition, a rule for relinquishing anengine can be established based on the average queue size falling belowa specified level over the specified time period. FIG. 5C illustrates apolicy wizard web page of the administrative interface that may be usedfoe setting statistical rule-based constraints.

The broker 30 allocates engines (or application server instances) todomains based on a current active policy and current applicationperformance statistics. The broker reevaluates and reapplies this policyperiodically (for example, every 5 minutes), and then decides to takeone of three courses of action: a) to make no change in the currentallocation, b) to assign available engines to some domains, or c) tore-assign some engines from some domains to other domains. FIG. 5Dillustrates an allocation of engines across domains.

Engines

As illustrated in FIGS. 1C and 6A, each engine in the AVP platform 100manages a container 30 to host and run a domain. Further, as illustratedfor example in FIG. 6A, an engine service instance 21 is managed by anengine daemon 22, both installed on a host computer 23.

Engines create service instances on demand, based on schedulingdecisions made by the broker. A service is created with the first clientrequest for an operation having the created service type. After creatingand running the requested operation, the engine stores the newly-createdservice in a cache. A scheduler is made aware of the contents of thecache, such that it will route other requests for that service to theengine.

By default, engines operate as single-threaded processes (“engineinstances”) performing only one service operation at a given time. As aresult, more than one engine instance 21 is generally running at onetime on the host computer 23. Processes running on multiple engineinstances are started and managed by an agent that also runs on the host(engine daemon 22).

Engine daemon 22 is capable of starting and stopping engines based on apre-defined engine policy. Engine policies may for example be based onone or more of CPU utilization of the host, user activity (in the casethat the host is a user's desktop) or time of day. In most cases, theengine daemon 22 starts and monitors engine instances 21, and restartsthe engine instances 21 in response to failures or reconfigurations.

One engine daemon 22 runs per host. In addition to starting engineinstances 21, the engine daemon 22 preferably controls the configurationof engine instances 21. For example, when changes to an engineconfiguration are made by a platform administrator (for example, toconfigure a new application server), the changes may be automaticallypropagated to an engine instance 21 via the engine daemon 22. Enginedaemons 22 may log into the broker 30 for administration andconfiguration.

Engine instances 21 are the processes that perform tasks for executingapplication software in the domain. On multi-CPU hosts, an engine daemon22 will be able to run multiple engine instances 21. In addition, morethan one engine instance 21 may be run on a single CPU.

Engines 20 report to the broker 30 when they are available to performwork. After logging in and synchronizing resources, the engines acceptwork assignments, perform tasks for executing the applications software,and notify the broker 30 when results are ready. Because the enginedaemon 22 controls the state of configuration for each engine instance21, and engine configuration can be controlled centrally via theadministrative interface of the broker, it is easy to control andconfigure engine instances across the computing resource grid.

Engines can be configured to run in a variety of modes, depending uponthe type of host machines 23 on which they will be installed. Dedicatedmachines are configure to run continuously, and are best suited forcomputing resources devoted to full-time processing on the grid. Anon-dedicated mode may be enabled for host machines that are only usedon a part-time basis on the grid, and otherwise used for other purposes(for example, user PCs sometimes made unavailable to the grid for userprocess use).

Engines configured in the non-dedicated mode determine when to run basedon two different modes. In the user interface (UI) idle mode, anon-dedicated engine will start running after user inactivity on thehost machine. Alternatively, in CPU idle mode, the engine will start torun when CPU utilization is sufficiently low. Engines are installed onlyonce on a host machine. As engines are centrally managed by an enginedaemon 22, they can be easily upgraded when later versions to the AVPplatform 100 are available by using the administrative interface. Inaddition, to gain additional efficiencies, configuration profiles may becreated by the administrative interface which may be used by multiplehost machines to synchronize configurations.

FIG. 6B provides a flow diagram illustrating steps in the lifecycle ofand engine. At step 601, the engine daemon 22 determines that an engineinstance should be running on the host 23 based on a state of the host23 and an engine mode of the host (for example, if the engine isnon-dedicated, an engine instance may be created only if no other userprocesses are currently running on the host 23). At step 602, the engineinstance 21 established a connection to the broker 30 to identify to thebroker 30 that the instance 21 is ready for work. At step 603, thebroker 30 provisions the engine instance 21 to a domain.

At step 604, a client, having received information relating to theengine instance 21 and its associated domain from the broker 30,connects to the engine instance to run a service. At step 605, when theservice has completed, the engine instance establishes anotherconnection to the broker 30 to indicate that it has completed theservice and to request another assignment.

At step 607, if the engine instance 21 is interrupted or otherwise failsgracefully, it connects to the broker 30 to send a message indicatingthat it has logged out. Otherwise, if the engine instance 21 failsunexpectedly, an engine monitor of the broker will log the engineinstance off. In either case, if available, the broker will provisionanther engine instance to the associated domain to replace the failedinstance.

Clients

As illustrated in FIG. 1A, requests for access to service domains 40 maybe forwarded to the broker 30 by Java clients 10 a. The clients 10 a forexample may make a request to invoke a method for processing in aservice domain using simple application programming interface (API)access. In the case of web domains, a web client 10 b (for example, aweb browser or other http client) may access a web application or webservice via Vgateway 31. In this case, the client simply opens a uniformresource locator (URL) that is directed to Vgateway 31, and configuredto run the selected application, virtualized on a web domain.

As illustrated for example in FIG. 7A, a client 10 synchronously invokesa method for processing in a service domain by sending an invocationmessage including service/method call information and a wait lock to acorresponding service domain 11. The service domain 11 adds the messageto an invocation queue 12. A thread running on the engine 20 is thenblocked by the service domain 11 using the wait lock. The process forasynchronous invocation is similar, except a result listener message issent in the invocation message, indicating that a listening process willbe created by the client and wait until the engine 20 indicates that thetask has been completed.

Communications between the engine 20 and the client 10 are managed by anengine proxy 13. As illustrated in FIG. 7B, the engine proxy 13 createsa new thread 14 for each thread 24 that has been started on the engine20. With these threads, the proxy 13 continuously asks for a nextinvocation process. The threads 14 will block if the queue 12 is empty.If the proxy 13 fails to process an invocation, it notifies the queuemanager 16, which places the unprocessed invocation back in the queue12.

Each client 10 has a performance monitor (not shown) for monitoring callrequests and keeping statistics on recent history. Request statisticsmonitored by the client 10 preferably include but are not necessarilylimited to total response time, time in the queue 12, time in transportand time in user code (i.e., direct application or service processingtime). The client monitor calculates average statistics for each of themeasured statistics, as well as average throughput. The averagestatistics are periodically sent by the client 10 to the broker 30, asfurther described herein.

Broker

The broker 30 provides policy-driven resource allocation and monitoringfor the AVP platform 100. Specific broker tasks include message routingand client authentication, engine allocation, engine provisioning andresource management, performance monitoring, and application andapplication server code distribution. Engines and clients are able tolog in to the broker 30 in support of these tasks.

FIG. 8A schematically illustrates a broker-driven process by whichengines are allocated to domains. Client 10 periodically sends averagestatistics to broker 30, which are received by statistics manager 33 andplaced in client and engine statistics queues 34. Engine allocator 32scans client and engine statistics queues at regular intervals, appliespolicy-based optimization algorithm 37, and decides either to make nochanges to the current allocation of engines to clients 10, to assigncurrently available engines from engine pool 35 to some of the clients10, and/or to re-assign some engines previously assigned to clients 10to other clients. Clients 10 are provided access to engines in enginepool 35 with the delivery of associated engine proxies 36 from thebroker 30 to the clients 10.

The broker 30 provisions engines according to the service policy basedon the operational mode of the broker, allocation policies and clientactivity. Schemas include “broker-initiated” provisioning and“client-initiated” provisioning). Broker-based provisioning is usefulfor controlling engine allocation across domains, and is required toenable engine sharing.

As illustrated in FIG. 8B, broker-based provisioning begins with aservice domain-specific request transmitted by a client 10 to the broker30. In response, the broker provides the client with an engine proxythat is already assigned to a specific service domain. With broker-basedprovisioning, a client may not directly ask the engine to change theassigned domain.

Two kinds of engine allocation are supported by broker-basedprovisioning. With exclusive allocation, as illustrated in FIG. 8B,engines are assigned with the delivery of associated engine proxies 36to clients 10 such that each engine 20 provisioned in a domain 40 isassigned to perform work for exactly one client 10. With sharedallocation, as illustrated in FIG. 8C, two or more clients 10 a, 10 a′may respectively use shared engine proxies 36 a, 36 b to send requeststo the same engine 20 in domain 40.

As illustrated in FIG. 8D, under the client-initiated provisioningschema, clients 10 receive “blank slate” engine proxies 36 c, and areable to provision them with service domains of their choice. A servicedomain-independent request is first transmitted by the client 10 to thebroker 30. In response, the broker 30 provides the client withunassigned proxy 36 c, allowing the client to activate a service domainof its choice via engine 20. Under this schema, no sharing of engines ispossible.

The broker performs a number of additional functions on behalf of theAVP platform 100. For example, the broker configures and stores avariety of operational settings and parameters, including but notnecessarily limited to user identification, passwords, clientinformation, routing properties and engine configuration. Using thisstored data, for example, associated tasks may be carried out byplatform administrators via the administrative interface of the broker30.

An internal database of the broker stores reporting data, including forexample user, engine, client and broker information, and an externalreporting database is used to log events and performance statistics.Associated database configurations may be managed by platformadministrators via the administrative interface.

Domain resources are staged on the broker 30, for deployment to engines.For example, files may be uploaded to deploy service, web and datadomains using the domain wizard component of the administrativeinterface as illustrated in FIG. 2. Domains can be deployed at the timeof uploading, or can be deployed or undeployed at a later time.

Monitoring and Statistics Tracking

The broker 30 carries out a performance monitoring function with theassistance of the clients 10 and engines 20. FIG. 9A schematicallyillustrates how the function is performed.

At regular intervals, the broker 30 asks at least one of each client 10and engine 20 associated with service and web domains (preferably, atleast each engine 20) to collect and forward averaged performancestatistics. The information is collected and forwarded by at least oneof a statistics collector 10 c of the client 10 and a statisticscollector 20 c of the engine 20 to the statistics manager 33 of thebroker 30. This process may for example be facilitated by means of a JMXproxy for clients and engines running J2EE applications.

FIG. 9B further illustrates schematically how statistics are collectedby the client 10 and engine 20. The statistics collectors 10 c, 20 c ofthe client 10 and engine 20 hold a collection of statistics providers60. At regular intervals, the statistics collector 10 c, 20 c asks eachprovider 60 to format its latest average statistics into a commonstatistics record 61, and forwards the common statistics records 61 tothe statistics manager 33 of the broker 30 as illustrated in FIG. 9A.The forwarded information includes an invoking group, domain, serviceand method “signature,” as well as the average values of collectedstatistics.

The statistics manager 33 places the forwarded information in client andengine statistics queues 34 of FIG. 9A. Periodically (for example,hourly), statistics persister 38 consolidates the collected data byaveraging the accumulated data for each client 10 and engine 20,calculating statistics for the entire computing resource grid, andstoring the calculated statistics in grid usage statistics database 39.Additional averaging and archiving is preferably performed periodicallyon the database 39 to further consolidate the data. The accumulated datain the database 39 may be displayed on a reporting screen 50 via the AVPplatform administrative interface.

A sample list of statistics tracked is provided in FIGS. 9C and 9D.Statistics used will vary according to application. For example, load ona JAVA application serve may be assessed by statistics such as queuedepth, service throughput or thread count rather than user responsetime.

With frequent collection of statistics from each client 10 and engine20, large amounts of statistical data accumulate. Accordingly, atfrequent intervals, the broker operates to average the data collectedfor each client and engine, to calculate statistics for the entire grid,and to save the resulting records in the broker databases. Archiving maybe performed after successive intervals, using similar averagingmethods.

The collected statistics may be viewed in a variety of ways via trackingtools in the administrative interface of the broker 30. As illustratedin FIG. 9E, for example, the administrative interface may include adashboard for displaying a variety of statistical data in summary form.The dashboard may provide, for example, pie charts indicating domain andgroup allocations of engines, measured statistics for the clients andengines, and platform alerts generated according to a comparison of themeasured statistics to service level agreements (SLAs) defined in theservice-level policies. In addition, the dashboard may provide links forviewing domains, wizards for configuring various components of theplatform, and links to other frequently used pages of the administrativeinterface.

For example, as illustrated in FIG. 9F, a web page of the administrativeinterface illustrates a thread count over time for a selected engine.

Adaptive Provisioning

FIG. 10 summarizes the adaptive provisioning process according to thepresent invention. As described above, at step 1010, a service-levelpolicy is defined and stored in a database 39 accessible to the broker30. The policy includes minimum and maximum resource levels to beallocated, for example, to a domain or user group, by time of day. Thepolicy may also include priority weights to be applied in the event ofresource contention, and service-level policies relating to measuredstatistics for the system.

At step 1020, the resources are provisioned according to the policy.Engines are assigned to domains by the broker 30, and configured bydownloading and installing associated application server and applicationsoftware in the engines. Once configured, engine instances are alsostarted in response to the receipt of service requests, and stopped upontask completion.

At step 1030, the broker 30 periodically collects averaged performancestatistics from one or more of the clients and the engines, and comparesthe averaged statistics with service-level agreements (SLAs) 1035defined in service-level policies. The statistics may provide measuresof throughput, response time, CPU occupancy, memory occupancy and otherattributes that may for example be defined as JMX attributes. In theevent that SLAs are not being met, the policy is again applied at step1010 and the resources are reallocated at step 1020. In addition, atstep 1040, alerts indicating violation of the SLAs may preferably bereported to administrators via a “dashboard” of the administrativeinterface of the broker 30.

Thus, while there have been shown, described, and pointed outfundamental novel features of the invention as applied to a preferredembodiment thereof, it will be understood that various omissions,substitutions, and changes in the form and details of the devicesillustrated, and in their operation, may be made by those skilled in theart without departing from the spirit and scope of the invention. Forexample, it is expressly intended that all combinations of thoseelements and/or steps which perform substantially the same function, insubstantially the same way, to achieve the same results are within thescope of the invention. Substitutions of elements from one describedembodiment to another are also fully intended and contemplated. It isalso to be understood that the drawings are not necessarily drawn toscale, but that they are merely conceptual in nature. It is theintention, therefore, to be limited only as indicated by the scope ofthe claims appended hereto.

All references, publications, pending and issued patents are herein eachincorporated by reference in their entirety.

1. A system for provisioning a shared computing infrastructure thatsupports a plurality of software applications and a plurality of typesof applications servers, each type of applications server providing arun-time environment for executing at least one of the plurality ofsoftware applications, the system comprising: two or more computingengines each assigned to execute an instance of one of the plurality ofsoftware applications in a run-time environment provided by one of theplurality of types of application servers; two or more clients eachaccessing one of the two or more computing engines to execute thesoftware application assigned to the one computing engine; and a brokerincluding: an optimization module for periodically determining anoptimal allocation of the plurality of software applications andapplications servers among the two or more computing engines; and aconfiguration manager for instructing one of the two or more computingengines to reconfigure by halting a current instance of a softwareapplication of a first type, and by loading and starting an instance ofa software application of a second type, wherein the softwareapplication of the first type operates in a run-time environment createdby a first type of software application server and the softwareapplication of the second type operates in a run-time environmentcreated by a second type of software application server.
 2. The systemof claim 1, wherein the broker further includes an engine allocationmodule for providing each of the two or more clients with an engineproxy for accessing its assigned computing engine.
 3. The system ofclaim 1, further comprising: a router that routes service requests fromthe two or more clients to the two or more computing engines, the routerbeing operative to balance at least one of a number of service requestsinitiated by the two or more clients and a service load resulting fromthe requests among the two or more computing engines.
 4. The system ofclaim 1, wherein the broker further includes: a monitor for collectingstatistical information from at least one of the two or more clients,the two or more engines and the router, wherein the optimization moduleperiodically determines the optimal allocation based on the statisticalinformation collected by the monitor and a defined policy.
 5. The systemof claim 4, wherein the optimization module further includes a policymanager for determining rules associated with the defined policy, and arules engine for capturing the determined rules.
 6. The system of claim1, wherein the broker further includes a software distribution modulefor distributing and loading instances of the two or more applicationsservers and instances of the two or more software applications on onesof the two or more computing engines.
 7. The system of claim 6, furthercomprising an archival database for storing components of the two ormore applications servers and the two or more software applications forretrieval by the software distribution module.
 8. The system of claim 5,further comprising an administrative interface for performing at leastone function selected from the group consisting of creating and editingsoftware applications, selecting software application servers forsoftware applications, creating and editing policies for softwareapplications, testing software applications and generating reports basedon the statistical information.
 9. A method for provisioning a sharedcomputing infrastructure that supports a plurality of softwareapplications and a plurality of types of applications servers, each typeof applications server providing a run-time environment for executing atleast one of the plurality of software applications, the methodcomprising the steps of: allocating each of two or more computingengines to execute an instance of one of the plurality of softwareapplications in a run-time environment provided by one of the pluralityof types of applications servers; instructing one of the two or morecomputing engines to reconfigure by halting a current instance of asoftware application of a first type, and by loading and starting aninstance of a software application of a second type, wherein thesoftware application of the first type operates in a run-timeenvironment created by a first type of software applications server, andthe software application of the second type operates in a run-timeenvironment created by a second type of software applications server.10. The method of claim 9, further comprising the step of: providing aclient with an engine proxy for accessing one of the two or morecomputing engines.
 11. The method of claim 9, further comprising thesteps of: routing service requests from two or more clients via agateway router to the two or more computing engines, the gateway routerbeing operative to balance at least one of a number of service requestsand a service load among the two or more computing engines.
 12. Themethod of claim 11, further comprising the steps of collectingstatistical information from at least one of the two or more clients,the two or more engines and the router, and periodically determining anoptimal allocation of the two or more computing engines to the pluralityof software applications and applications servers based on the collectedstatistical information and a defined policy.
 13. The method of claim12, wherein the defined policy includes at least one of a minimum numberof the two or more computing engines to be assigned to one of theplurality of software applications and a maximum number of the two ormore computing engines to be assigned to one of the plurality ofsoftware applications.
 14. The method of claim 13, wherein the definedpolicy includes a policy schedule having one or more time of daypolicies.
 15. The method of claim 9, further comprising the steps of:storing components of the two or more applications servers and theplurality of software applications in an archival database; retrievingcomponents from the archive database that define the softwareapplication of the second type and applications server of the secondtype, the retrieved components to be loaded by the one computing engine;and registering the software application of the second type andapplications server of the second type in association with a domain. 16.The method of claim 15, wherein the domain has a domain type selectedfrom the group consisting of service domains, web domains and datadomains.
 17. The system of claim 4, wherein the optimization moduledetermines the optimal allocation based further on priorities assignedto each of the plurality of software applications.
 18. The method ofclaim 12, wherein the optimal allocation is further based further onpriorities assigned to each of the plurality of software applications.